package tar

import (
	"errors"
	"fmt"
	"io"
	"io/fs"
	"maps"
	"path"
	"slices"
	"strings"
	"time"
)

// Writer provides sequential writing of a tar archive.
// [Writer.WriteHeader] begins a new file with the provided [Header],
// and then Writer can be treated as an io.Writer to supply that file's data.
type Writer struct {
	w    io.Writer
	pad  int64      // Amount of padding to write after current file entry

	scannerVersionsScannedMD = NewCounterMD(scannerVersionsScanned,
		"Total number of object versions scanned since server start")
	scannerLastActivitySecondsMD = NewGaugeMD(scannerLastActivitySeconds,
		"Time elapsed (in seconds) since last scan activity.")
)

// loadClusterScannerMetrics - `MetricsLoaderFn` for cluster webhook
// such as failed objects and directories scanned.

package sql

import (
	"testing"
	"time"
)

func TestParseAndDisplaySQLTimestamp(t *testing.T) {
	beijing := time.FixedZone("", int((8 * time.Hour).Seconds()))
	fakeLosAngeles := time.FixedZone("", -int((8 * time.Hour).Seconds()))
	cases := []struct {
		s string
		t time.Time
	}{
		{"2010T", time.Date(2010, 1, 1, 0, 0, 0, 0, time.UTC)},
		{"2010-02T", time.Date(2010, 2, 1, 0, 0, 0, 0, time.UTC)},

// ExtractFunc represents EXTRACT sql function
type ExtractFunc struct {
	Timeword string       `parser:" \"EXTRACT\" \"(\" @( \"YEAR\":Timeword | \"MONTH\":Timeword | \"DAY\":Timeword | \"HOUR\":Timeword | \"MINUTE\":Timeword | \"SECOND\":Timeword | \"TIMEZONE_HOUR\":Timeword | \"TIMEZONE_MINUTE\":Timeword ) "`
	From     *PrimaryTerm `parser:" \"FROM\" @@ \")\" "`
}

// TrimFunc represents TRIM sql function
type TrimFunc struct {

    }
  }

  /** Returns once all stream actions complete successfully. */
  fun awaitSuccess() {
    val futureTask =
      results.poll(5, TimeUnit.SECONDS)
        ?: throw AssertionError("no onRequest call received")
    futureTask.get(5, TimeUnit.SECONDS)
  }

      implements Serializable {
    final Converter<A, B> first;
    final Converter<B, C> second;

    ConverterComposition(Converter<A, B> first, Converter<B, C> second) {
      this.first = first;
      this.second = second;
    }

    /*
     * These gymnastics are a little confusing. Basically this class has neither legacy nor

the current user is joined to a slow domain, which is the
usual case for many corporate users. The new implementation
performance is now in the order of milliseconds, compared to
the previous implementation which could take several seconds,

pkg p4, func NewPair[$0 interface{ M }, $1 interface{ ~int }]($0, $1) Pair[$0, $1]
pkg p4, method (Pair[$0, $1]) Second() $1
pkg p4, method (Pair[$0, $1]) First() $0
pkg p4, type Pair[$0 interface{ M }, $1 interface{ ~int }] struct
pkg p4, func Clone[$0 interface{ ~[]$1 }, $1 interface{}]($0) $0

	for {
		if err := sm.load(ctx, newObjectLayerFn()); err == nil {
			<-ctx.Done()
			return
		}
		duration := time.Duration(r.Float64() * float64(time.Second*10))
		if duration < time.Second {
			// Make sure to sleep at least a second to avoid high CPU ticks.
			duration = time.Second
		}
		time.Sleep(duration)
	}
}

// load resync metrics saved on disk into memory

@ElementTypesAreNonnullByDefault
public class AbstractIteratorTest extends TestCase {

  public void testDefaultBehaviorOfNextAndHasNext() {

    // This sample AbstractIterator returns 0 on the first call, 1 on the
    // second, then signals that it's reached the end of the data
    Iterator<Integer> iter =
        new AbstractIterator<Integer>() {
          private int rep;

          @Override
          public @Nullable Integer computeNext() {